Download Questions 1 Question 3.2–1: (Solution, p 2) Represent - 300 and

Questions
Question 3.2–1: (Solution, p 2) Represent
sentation.
Question 3.2–2: (Solution, p 2) Represent
representation.
1
300 and
300 and
1 in twelve bits using sign-magnitude repre1 in twelve bits using two’s-complement
Question 3.2–3: (Solution, p 2) What is the smallest (most negative) number you can represent in twelve
bits using sign-magnitude representation? In two’s-complement representation? Give both the bit pattern of
the number and its decimal translation.
Question 3.3–1: (Solution, p 2) Convert each of the following numbers to the 8-bit floating-point representation we saw in class.
a. 2.5 b. 0.0625 Question 3.3–2: (Solution, p 2) What decimal number does each of the 8-bit floating-point bit patterns
represent?
a. 0 0110 101
b. 1 1011 001
Question 3.3–3: (Solution, p 2) For the following questions, we define an nine-bit floating point number to
include one sign bit, five exponent bits (using excess 15), and three mantissa bits. The all-zeroes exponent
is reserved for denormalized numbers, and the all-ones exponent is reserved for the special cases.
a. Represent each of the following decimal numbers in this nine-bit system: 1 ,
6 .
b. Convert each of the following nine-bit floating-point patterns into base 10. Your answer should include
at least two significant digits.
0 10000 010
1 10011 110
c. Assuming that the system uses the special-case numbers (infinity, negative infinite, not-a-number),
what is the largest numerical value you can represent in this nine-bit system? Express your answer in
decimal and justify your answer.
Question 3.4–1: (Solution, p 2) Suppose a digital camera uses a MB disk to store pictures. How many
-inch photographs can it store in 24-bit color at the standard printer-quality resolution of 300 pixels per
inch?
Question 3.4–2: (Solution, p 2) We examined a compression technique called run-length encoding for
black-and-white images, in which each byte includes four bits saying how many adjacent black pixels there
are and four bits saying how many adjacent white pixels there are. As we saw, this compression technique
sometimes actually expands a picture. What is the maximum possible expansion factor?
Solutions
2
Solution 3.2–1: (Question, p 1) 1001 0010 1100 is
300 and 1000 0000 0001 is
1 .
Solution 3.2–2: (Question, p 1) 1110 1101 0100 is
300 and 1111 1111 1111 is
1 .
Solution 3.2–3: (Question, p 1)
Sign-magnitude: 1111 1111 1111 represents
2,047 Two’s-complement: 1000 0000 0000 represents
2,048 Solution 3.3–1: (Question, p 1)
a. 0 1000 010
b. 0 0011 000
Solution 3.3–2: (Question, p 1)
a. 0.8125 b.
18 Solution 3.3–3: (Question, p 1)
.
.
a.
work
b.
problem
0 10000 010
1 10011 110
solution
0 01111 000
1 10001 100
solution
2.5 1.010 10.1 28 1.110 11100 c. To get the largest number, the exponent bits willbe
11110 (11111 being reserved for the non-numbers)
61,440 0000 and the mantissa bits will be 111. 1.111 Solution 3.4–1: (Question, p 1)
sq. inches
picture
pixels
sq. inch
bytes
pixel
MB bytes
MB
picture
MB picture pictures
MB
disk
disk
(Of course, since it wouldn’t store a fraction of a picture, It would only hold 10 pictures.)
Solution 3.4–2: (Question, p 1) A checkboard pattern, where every other pixel is black, would give the
maximum expansion factor. For such a system, each run would be only one pixel long, and the compression
system would use four bits to encode each run, for an expansion factor of four.